The present invention relates generally to network and Internet search and interface systems and more particularly to search systems that provide enhanced search functionality including functions wherein search queries are automatically categorized according to one or more taxonomies and wherein taxonomies can be automatically generated from past queries and/or user actions in relation to the queries.
With the advent of the Internet and the multitude of web pages and media content available to a user over the World Wide Web (web), there has become a need to provide users with streamlined approaches to filter and obtain desired information from the web. Search systems and processes have been developed to meet the needs of users to obtain desired information. Examples of such technologies can be accessed through Yahoo!, Google and other sites. Typically, a user inputs a query and a search process returns one or more links (in the case of searching the web), documents and/or references (in the case of a different search corpus) related to the query. The links returned may be closely related, or they may be completely unrelated, to what the user was actually looking for. The “relatedness” of results to the query may be in part a function of the actual query entered as well as the robustness of the search system (underlying collection system) used. Relatedness might be subjectively determined by a user or objectively determined by what a user might have been looking for.
Queries that users enter are typically made up of one or more words. For example, “Hawaii” is a query, so is “New York city”, and so is “New York city law enforcement”. As such, queries as a whole are not integral to the human brain. In other words, human beings do not naturally think in terms of queries. They are an artificial construct imposed, in part, by the need to query search engines or look up library catalogs. Human beings do not naturally think in terms of just single words either. What human beings think in terms of are natural concepts. For example, “Hawaii” and “New York city” are vastly different queries in terms of length as measured by number of words but they share one important characteristic: they are each made up of one concept. The query “New York city law enforcement” is different, however, because it is made up of two distinct concepts “New York city” and “law enforcement”.
Human beings also think in terms of logical relationships between concepts. For example, “law enforcement” and “police” are related concepts since the police are an important agency of law enforcement; a user who types in one of these concepts may be interested in sites related to the other concept even if those sites do not contain the particular word or phrase the user happened to type. As a result of such thinking patterns, human beings by nature build queries by entering one or more natural concepts, not simply a variably long sequence of single words, and the query generally does not include all of the related concepts that the user might be aware of. Also, the user intent is not necessarily reflected in individual words of the query. For instance, “law enforcement” is one concept, while the separate words “law” and “enforcement” do not individually convey the same user intent as the words combined.
Current technologies used by search providers do not understand queries the same way that human beings create them. For instance, existing search engines generally search for the exact words or phrases the user entered, not for the underlying natural concepts or related concepts the user actually had in mind. This is perhaps the most important reason that prevents search providers from identifying a user's intent and providing optimal search results and content.
As can be seen there is a need for improved search and interface technology that aids in providing results that are more in line with the actual concepts in which a user may be interested and a better user experience.